AIMC Topic: Databases, Factual

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Hierarchical Multi-Class Group Correlation Learning Network for Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Hierarchical approaches have been tremendously successful at multi-label segmentation. However, it has been shown they may seriously suffer from the problem of only imposing constraints on shallow layers while ignoring deep relationships in the label...

ISGAN: Unsupervised Domain Adaptation With Improved Symmetric GAN for Cross-Modality Multi-Organ Segmentation.

IEEE journal of biomedical and health informatics
The differences between cross-modality medical images are significant, so several studies are working on unsupervised domain adaptation (UDA) segmentation, which aims to adapt a segmentation model trained on a labeled source domain to an unlabeled ta...

SNER: Semi-Supervised Named Entity Recognition for Large Volume of Diabetes Data.

IEEE journal of biomedical and health informatics
The medical literature and records on diabetes provide crucial resources for diabetes prevention and treatment. However, extracting entities from these textual diabetes data is crucial but challenging. Named entity recognition (NER) - an important co...

GAN Inversion for Data Augmentation to Improve Colonoscopy Lesion Classification.

IEEE journal of biomedical and health informatics
A major challenge in applying deep learning to medical imaging is the paucity of annotated data. This study explores the use of synthetic images for data augmentation to address the challenge of limited annotated data in colonoscopy lesion classifica...

GenECG: a synthetic image-based ECG dataset to augment artificial intelligence-enhanced algorithm development.

BMJ health & care informatics
OBJECTIVES: An image-based ECG dataset incorporating visual imperfections common to paper-based ECGs, which are typically scanned or photographed into electronic health records, could facilitate clinically useful artificial intelligence (AI)-ECG algo...

DeepMBEnzy: An AI-Driven Database of Mycotoxin Biotransformation Enzymes.

Journal of agricultural and food chemistry
Mycotoxins are toxic fungal metabolites that pose significant health risks. Enzyme biotransformation is a promising option for detoxifying mycotoxins and for elucidating their intracellular metabolism. However, few mycotoxin-biotransformation enzymes...

Data Exploration for Target Predictions Using Proprietary and Publicly Available Data Sets.

Chemical research in toxicology
When applying machine learning (ML) approaches for the prediction of bioactivity, it is common to collect data from different assays or sources and combine them into single data sets. However, depending on the data domains and sources from which thes...

Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data.

BMJ open
OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques t...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

Environmental pollution (Barking, Essex : 1987)
The rapid and accurate identification of antibiotics in environmental samples is critical for addressing the growing concern of antibiotic pollution, particularly in water sources. Antibiotic contamination poses a significant risk to ecosystems and h...

Classification of multi-lead ECG based on multiple scales and hierarchical feature convolutional neural networks.

Scientific reports
Detecting and classifying arrhythmias is essential in diagnosing cardiovascular diseases. However, current deep learning-based classification methods often encounter difficulties in effectively integrating both the morphological and temporal features...